UTLNet: Uncertainty-aware transformer localization network for RGB-depth mirror segmentation
Mirror segmentation, an emerging discipline in the field of computer vision, involves the
identification and marking of mirrors in an image. Current mirror segmentation methods rely …
identification and marking of mirrors in an image. Current mirror segmentation methods rely …
Cross-modality transformer with modality mining for visible-infrared person re-identification
The visible-infrared person re-identification (VI-ReID) is a challenging ReID task, which aims
to retrieve and match the same identity's images between the heterogeneous visible and …
to retrieve and match the same identity's images between the heterogeneous visible and …
Deep multimodal representation learning for generalizable person re-identification
Person re-identification plays a significant role in realistic scenarios due to its various
applications in public security and video surveillance. Recently, leveraging the supervised …
applications in public security and video surveillance. Recently, leveraging the supervised …
Image aesthetics assessment based on hypernetwork of emotion fusion
Research in psychology demonstrates that visual features and semantic content can convey
various emotions. Furthermore, studies have proved that image emotion and aesthetics are …
various emotions. Furthermore, studies have proved that image emotion and aesthetics are …
CalibNet: Dual-branch cross-modal calibration for RGB-D salient instance segmentation
In this study, we propose a novel approach for RGB-D salient instance segmentation using a
dual-branch cross-modal feature calibration architecture called CalibNet. Our method …
dual-branch cross-modal feature calibration architecture called CalibNet. Our method …
KepSalinst: Using peripheral points to delineate salient instances
Salient instance segmentation (SIS) is an emerging field that evolves from salient object
detection (SOD), aiming at identifying individual salient instances using segmentation maps …
detection (SOD), aiming at identifying individual salient instances using segmentation maps …
Unsupervised Salient Instance Detection
The significant amount of manual efforts in annotating pixel-level labels has triggered the
advancement of unsupervised saliency learning. However without supervision signals state …
advancement of unsupervised saliency learning. However without supervision signals state …
Oamatcher: An overlapping areas-based network for accurate local feature matching
K Dai, T Xie, K Wang, Z Jiang, R Li, L Zhao - arXiv preprint arXiv …, 2023 - arxiv.org
Local feature matching is an essential component in many visual applications. In this work,
we propose OAMatcher, a Tranformer-based detector-free method that imitates humans …
we propose OAMatcher, a Tranformer-based detector-free method that imitates humans …
DPNet: Detail-preserving image deraining via learning frequency domain knowledge
The quality of images captured in rainy days is severely degraded, which affects the
accuracy of subsequent computer vision tasks. Recently, many deep learning-based …
accuracy of subsequent computer vision tasks. Recently, many deep learning-based …
End-to-end video scene graph generation with temporal propagation transformer
Video scene graph generation has been an emerging research topic, which aims to interpret
a video as a temporally-evolving graph structure by representing video objects as nodes …
a video as a temporally-evolving graph structure by representing video objects as nodes …